Search Results (85)

Background: Coronary bifurcation lesions represent one of the most technically demanding scenarios in coronary artery disease (CAD), associated with higher procedural complexity, restenosis, and periprocedural complications. Recent advances in coronary computed tomography angiography (CCTA) have markedly improved its ability to visualize complex coronary anatomy, assess plaque morphology, and guide revascularization. Objectives: This review summarizes (1) technological advances in CCTA over the last decade, (2) its role in evaluating bifurcation stenosis, (3) assessment of plaque morphology and distribution, (4) quantification of bifurcation geometry, and (5) emerging evidence supporting its application in revascularization planning and guidance. Findings: Modern wide-detector and dual-source CT systems, iterative and deep-learning reconstruction algorithms, and photon-counting CT (PCCT) have significantly improved temporal and spatial resolution, reduced blooming artifacts, and lowered radiation dose. CCTA now reliably quantifies bifurcation stenosis and plaque distribution, characterizes high-risk plaque features, and accurately measures bifurcation angles. The integration of CT-derived fractional flow reserve (FFR-CT) and artificial intelligence (AI)-based plaque quantification further strengthens its diagnostic and prognostic performance. CCTA-derived bifurcation scores and 3D modelling support procedural strategy selection, stent sizing, and side-branch (SB) protection. Conclusions: CCTA has evolved into a comprehensive tool for non-invasive diagnosis, physiological assessment, and pre-procedural planning of bifurcation disease. With the advent of PCCT and AI-enhanced quantitative tools, CCTA is poised to become a central component of revascularization decision-making in complex coronary bifurcations. Full article

Introduction: Detection of in-stent restenosis by cardiac CT is challenging due to blooming artifacts. The technological progress of CT scanners and especially the recent introduction of photon-counting detectors (PCDs) has led to an improvement in image quality. Several studies have analyzed the lumen visibility of coronary stents, but most studies used models which did not simulate cardiac movement. In this study we use a pulsatile heart model to simulate a heartbeat to analyze the effects of cardiac motion on image quality. Methods: Seventeen different coronary stents with an outer diameter of 3.0 mm were implanted into polyolefin tubes. The tubes were then filled with diluted contrast medium and attached to the pulsatile heart model. The stents were scanned in a third-generation dual-source CT with an energy-integrating detector (EID) and a first-generation PCD CT. Results: In motion, the mean visible stent lumen was reduced from 64.4% to 59.4% in EID CT, from 61.4% to 56.0% in PCD CT using the Bv60 kernel, and from 72.9% to 62.9% in PCD CT using the Bv72 kernel, each in standard resolution mode. Employing the ultra-high-resolution mode (UHR), stent lumen visibility was reduced from 61.3% to 57.9% with the Bv60 kernel and from 71.7% to 61.8% with the Bv72 kernel. The difference between static imaging and motion was significant in each instance (p < 0.001). Conclusions: While PCD CT and the use of sharper kernels improves the image quality in comparison with EID CT and smoother kernels, the impact of cardiac motion on the reduction in stent lumen visibility is substantial. Hence, the best image quality is achieved in patients with a normal and regular heart rate. If this is not possible to achieve, a retrospective acquisition mode should be considered. Full article

Background/Objectives: To determine the optimal reconstruction parameters for accurate visualization of peripheral in-stent restenosis using photon-counting detector CT (PCD-CT), and to evaluate its potential advantages over energy-integrated detector CT (EID-CT). Methods: Endovascular peripheral stents with varying degrees of in-stent restenosis were scanned in a custom-made phantom using EID-CT (Somatom Force) and PCD-CT (Naeotom Alpha) under clinical acquisition protocols. EID-CT images were reconstructed with Bv40 and Bv59 kernels at 512 matrices. PCD-CT data were acquired in standard-resolution (SR) and ultra-high-resolution (UHR) modes. In both modes, images were reconstructed with multiple kernels (Bv40, Bv56 and Bv72) and matrix sizes (512 and 1024 matrix). In SR mode, additional virtual monoenergetic images (40–100 keV) were generated, while UHR mode included only polychromatic reconstructions. Quantitative image quality (noise, contrast, contrast-to-noise ratio [CNR]) was measured, and two blinded readers performed qualitative assessments of restenosis visualization. Results: PCD-CT with SR mode at VMI 40 keV achieved the highest image contrast and CNR, significantly outperforming EID-CT and PCD-CT_UHR under matched conditions (all p < 0.05). The sharper reconstruction kernel further enhanced the image contrast and improved subjective visualization despite increased image noise. Both readers ranked PCD-CT_{SR-Bv72-40keV} at 1024 matrix highest for detecting all degrees of restenosis, with excellent inter-reader agreement (ρ > 0.80). Conclusions: PCD-CT in SR mode at VMI 40 keV, specifically using the Bv72 kernel with a 1024 matrix, optimizes the visualization of peripheral in-stent restenosis. Compared to EID-CT, PCD-CT provides superior image quality and detectability of restenosis. Full article

Objective: To evaluate the performance of photon-counting detector CT (PCD-CT) angiography for the detection and quantification of vascular stenosis. Methods: Web of Science, PubMed, and Cochrane databases were searched from January 1980 to December 2025 to identify studies assessing PCD-CT angiography for the detection and quantification of vascular stenosis, using invasive angiography as the reference standard. The risk of bias of the included studies was assessed using the Quality Assessment of Diagnostic Accuracy Studies-2 (QUADAS-2) tool. Diagnostic performance metrics, including sensitivity and specificity and quantification values, were extracted from the included studies and a formal narrative synthesis was performed. The meta-analysis included studies reporting true-positive, false-positive, true-negative, and false-negative data. A meta-analysis was conducted only when a minimum of two eligible studies assessed diagnostic performance within the given vascular territory. Statistical analyses were performed using R software (v4.5.0), applying a random-effects model for the meta-analysis. Results: Of 415 identified studies, 20 were included in the systematic review, comprising a total of 9165 participants, with the majority (17/20, 85%) focusing on coronary artery stenosis. In the meta-analysis of three studies, ultra-high-resolution (UHR) PCD-CT demonstrated excellent diagnostic performance for detecting coronary stenosis for patients with ≥50%, having a pooled sensitivity of 96.1% (95% confidence level (CI): 89.3–99.6), specificity of 87.5% (95% CI: 78.2–93.3), positive predictive value (PPV) of 91.9% (95% CI: 70.3–98.2), and negative predictive value (NPV) of 94.8% (95% CI: 86.0–98.6). Compared with conventional energy-integrating detector CT (EID-CT), PCD-CT consistently showed superior diagnostic performance, particularly in the specificity and PPV. In terms of stenosis quantification, PCD-CT showed closer agreement with reference standards than EID-CT, leading to the reclassification of coronary stenosis severity in up to 49% of patients. Evidence for non-coronary vascular territories, including intracranial and peripheral arteries remains limited but suggests promising diagnostic performance. For lower-limb arterial stenosis, the reported sensitivity was 77.4–91%, and specificity was 72.1–91%. For intracranial in-stent stenosis, PCD-CT demonstrated a sensitivity of 100% and a specificity of 89%. Conclusions: PCD-CT angiography provides high diagnostic performance and improved stenosis quantification for coronary artery stenosis. UHR PCD-CT has excellent diagnostic performance for detecting coronary stenosis and consistently outperforms conventional EID-CT, especially in the specificity and positive predictive value. Full article

Background/Objectives: There is an increasing need for cross-sectional imaging in pediatric patients with congenital heart disease. This patient group is highly sensitive to ionizing radiation. The purpose of this article was to evaluate differences in radiation dose and image quality between a first-generation photon-counting (PC)-CT system and a 256-slice single-source energy-integrating detector (EID)-CT in these patients. Methods: We retrospectively assessed effective dose, CT dose index-volume (CTDI_vol), dose length product (DLP), and image quality of all prospectively electrocardiography-gated CTs of the thorax in all patients < 18 years of age examined between February 2021 and August 2024 (n = 43). Two independent observers subjectively scored image quality, vascular contrast, and noise on a 5-point Likert scale. In addition, we assessed the signal-to-noise-ratio (SNR) and contrast-to-noise-ratio (CNR) quantitatively. Results: All dose parameters were significantly lower in the PC-CT (n = 27) versus the EID-CT (n = 16) group (mean effective dose: 0.8 ± 0.64 versus 2.2 ± 0.88 mSv, p < 0.001; mean CTDI_vol: 1.22 ± 0.96 versus 4.8 ± 1.08 mGy, p < 0.001; mean DLP: 30.7 ± 31.9 versus 73.7 ± 50.7 mGy*cm, p < 0.001). Overall subjective image quality and contrast were rated higher in the PC-CT group (p = 0.046 and < 0.001, respectively). Quantitative CNR was significantly higher in the PC-CT group (mean 39.1 ± 12.9 versus 26.2 ± 10.8, p = 0.002). Conclusions: PC-CT enables high-quality examinations for the evaluation of congenital heart disease with a highly significant dose reduction compared with a 256-slice single-source EID-CT. Full article

Background/Objectives: Aortic valve calcification is commonly evaluated using 3.0 mm true non-contrast (TNC) computed tomography (CT) images. This study evaluates the reproducibility of virtual non-contrast (VNC) reconstructions at different slice intervals using photon-counting detector CT (PCD-CT). Methods: In this retrospective study, we included 279 consecutive patients, who underwent PCD-CT for evaluation of native aortic valve between February 2023 and December 2023 with both TNC and VNC images at 3.0 and 1.5 mm slice intervals. Aortic valve calcium score (AVCS) and aortic valve calcium volume (AVCV) were compared between the two methods using paired t-tests. Agreement for continuous variables was assessed using inter-class coefficients (ICCs). Cohen’s Kappa (κ) was calculated to evaluate the agreement between different modalities in diagnosing severe AV calcification. Results: Compared to the standard, TNC images at 1.5 mm intervals showed higher AVCS (mean difference: −290 ± 418, p < 0.001), with high reproducibility between techniques (CS: ICC 0.969, [IQR 0.962, 0.975]). Compared with reference, VNC showed no significant differences in AVCS at either slice intervals, with excellent reproducibility (3.0 mm, ICC 0.970 [0.963, 0.976]; 1.5 mm, ICC 0.971 [0.964, 0.977]). Compared to TNC 3.0 mm, strong concordance was observed using other reconstruction techniques in assessing severe AV calcification (κ = 0.81 [95% CI: 0.74–0.88], 0.83 [95% CI: 0.76–0.90], and 0.83 [95% CI: 0.76–0.90] for TNC at 1.5 mm, VNC at 3.0 mm, and 1.5 mm, respectively), with low misclassification rates. Conclusions: Our study highlights high reproducibility in the evaluation of AVCS by VNC reconstruction at 3.0 and 1.5 mm intervals compared with reference offering a reliable alternative with an excellent diagnostic accuracy. Full article

Background: Photon-counting computed tomography (PCCT) represents a major technological advance in clinical CT imaging, offering superior spatial resolution, enhanced material discrimination, and potential radiation dose reduction compared to conventional energy-integrating detector systems. As the first clinically approved PCCT scanner becomes available, establishing a comprehensive characterization of its image quality is essential to understand its performance and clinical impact. Methods: Image quality was evaluated using a commercial quality assurance phantom with acquisition protocols typically used for three anatomical regions—head, abdomen/thorax, and inner ear—representing diverse clinical scenarios. Each region was scanned using both ultra-high-resolution (UHR, 120 × 0.2 mm slices) and conventional (144 × 0.4 mm slices) protocols. Conventional metrics, including signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), slice thickness accuracy, and uniformity, were assessed following international standards. Task-based analysis was also performed through target transfer function (TTF), noise power spectrum (NPS), and detectability index (d′) to evaluate diagnostic relevance. Results: UHR protocols provided markedly improved spatial resolution, particularly in the inner ear imaging, as confirmed by TTF analysis, though with increased noise and reduced low-contrast detectability in certain conditions. CT numbers showed linear correspondence with known attenuation coefficients across all protocols. Conclusions: This study establishes a detailed technical characterization of the first clinical PCCT scanner, demonstrating significant improvements in terms of spatial resolution and accuracy of the quantitative image analysis, while highlighting the need for noise–contrast optimization in high-resolution imaging. Full article

Background/Objectives: This study evaluates photon-counting CT (PCCT) for the imaging of mouse femurs and investigates how APOE genotype, sex, and humanized nitric oxide synthase (HN) expression influence bone morphology during aging. Methods: A custom-built micro-CT system with a photon-counting detector (PCD) was used to acquire dual-energy scans of mouse femur samples. PCCT projections were corrected for tile gain differences, iteratively reconstructed with 20 µm isotropic resolution, and decomposed into calcium and water maps. PCD spatial resolution was benchmarked against an energy-integrating detector (EID) using line profiles through trabecular bone. The contrast-to-noise ratio quantified the effects of iterative reconstruction and material decomposition. Femur features such as mean cortical thickness, mean trabecular spacing (TbSp_mean), and trabecular bone volume fraction (BV/TV) were extracted from calcium maps using BoneJ. The statistical analysis used 57 aged mice representing the APOE22, APOE33, and APOE44 genotypes, including 27 expressing HN. We used generalized linear models (GLMs) to evaluate the main interaction effects of age, sex, genotype, and HN status on femur features and Mann–Whitney U tests for stratified analyses. Results: PCCT outperformed EID-CT in spatial resolution and enabled the effective separation of calcium and water. Female HN mice exhibited reduced BV/TV compared to both male HN and female non-HN mice. While genotype effects were modest, a genotype-by-sex stratified analysis found significant effects of HN status in female APOE22 and APOE44 mice only. Linear regression showed that age significantly decreased cortical thickness and increased TbSp_mean in male mice only. Conclusions: These results demonstrate PCCT’s utility for femur analysis and reveal strong effects of sex/HN interaction on trabecular bone health in mice. Full article

This review focuses on the diverse etiologies of secondary spontaneous pneumothorax (SSP) and the crucial role of imaging in their diagnosis. Unlike primary spontaneous pneumothorax (PSP), which is typically due to ruptured blebs, SSP results from a wide array of underlying pulmonary conditions that can pose significant diagnostic challenges. These include infections like tuberculosis, airway diseases such as chronic obstructive pulmonary disease, malignancies (primary and metastatic), interstitial lung diseases like sarcoidosis, cystic lung diseases such as lymphangioleiomyomatosis, and connective tissue disorders. In women, catamenial pneumothorax secondary to endometriosis should be considered. The role of radiologists is crucial in uncovering these underlying conditions. While chest radiography is the initial imaging modality, computed tomography (CT) provides superior sensitivity for detecting subtle parenchymal abnormalities. Advanced techniques like photon-counting detector CT offer further benefits, including enhanced spatial resolution, reduced noise, and lower radiation dose, potentially revealing underlying causes that might be missed with conventional CT. This enhanced visualization of subtle parenchymal changes, small airways, and vascular structures can be the key to diagnosing the underlying cause of pneumothorax. Recognizing the diverse etiologies of SSP and utilizing advanced imaging techniques is paramount for accurate diagnosis, appropriate management, and improved patient outcomes. Full article

Background: Computed tomography (CT)-based image-guided surgery (IGS) is of great importance in functional endoscopic sinus surgery (FESS) and requires IGS-specific imaging protocols to ensure high intraoperative accuracy. This study aimed to compare photon-counting CT (PCCT), dual-energy dual-source CT (DECT), and spectral detector CT (SDCT) of the paranasal sinuses with respect to image quality, IGS accuracy and radiation dose. Methods: A formalin-fixed cadaver skull was examined using PCCT, DECT and SDCT at 100 kV tube voltage with descending tube currents (mAs). The setup of electromagnetic IGS was evaluated using a visual analog scale. Accuracy was analyzed endoscopically using defined anatomical landmarks. Diagnostic image quality as well as bone and soft tissue noise were assessed qualitatively using a 5-point Likert scale and quantitatively by determination of signal-to-noise ratio. Radiation dose was evaluated using the dose length product. Results: While PCCT datasets could be registered and navigated accurately down to 10 mAs (1.5 mm error at 10 mAs), both DECT and SDCT exhibited significantly increased inaccuracies below 40 mAs (4.35/5.15 mm for DECT/SDCT at 25 mAs). Using PCCT therefore enabled a 45% radiation dose reduction at the minimally required dose length product using PCCT. Quantitative and qualitative image quality were superior for PCCT compared to DECT and SDCT. Conclusions: PCCT provides excellent accuracy of anatomical landmarks in IGS with superior image quality of the paranasal sinuses in low-mA scans and substantially reduced radiation exposure. Full article

Background: Computed tomography (CT) is the standard of reference for diagnosis and follow-up in aortic dissection (AD). Localizing the entry and identifying false and true lumen are as important as differing post-treatment changes from contrast media extravasations. Photon-counting detector CT (PCDCT) allows for virtual monoenergetic (VME) reconstructions, which can augment contrast media effects on lower energy levels, and for virtual non-contrast (VNC) reconstructions. The aim of this study was to analyze the influence of VME reconstructions on contrast media effects in different dissection compartments as well as compare true and VNC series in AD patients. Methods: We retrospectively analyzed PCDCT datasets from 28 patients with aortic dissections, with different dissection types and different treatment statuses. Attenuation and standard deviation values of the ascending and descending aorta, as well as CT values of the false lumen, were measured. These measurements were obtained from VME images at energy levels ranging from 40 to 190 keV in 10 keV increments, as well as from non-contrast (NC) and VNC reconstructions. The signal-to-noise ratio (SNR) was calculated. Additionally, subjective values for dissection assessability and native aspects of the images were acquired for different reconstructions. Results: CT values decreased with higher energy levels in VME imaging. Ascending aorta showed higher attenuation values than descending aorta, which was higher than false lumen (e.g., at 70 keV ascending 357 [310; 419] HU, descending 346 [305; 401] HU and false lumen 298 [248; 363] HU). These differences increased on lower VME reconstructions with statistical significance for the comparisons of ascending and descending aorta with the false lumen on all energy levels. In line with this, SNR showed highest values for ascending aorta compared to descending aorta and false lumen on all energy levels. For NC comparisons, VNC and VME at 190 keV reconstructions showed higher CT values than NC reconstructions (e.g., overall data NC 48 [42; 55] HU, VNC 66 [57; 73] HU, 190 keV 97 [89; 105] HU). Subjective ratings were worse with VNC than with NC images. Conclusions: VME reconstructions on lower energy levels can be helpful in differentiating between true and false lumen in aortic dissections. Full article

Material decomposition in X-ray imaging is essential for enhancing tissue differentiation and reducing the radiation dose, but the clinical adoption of photon-counting detectors (PCDs) is limited by their high cost and technical complexity. To address this, we propose Dual-head Pix2Pix, a PCD-guided deep learning framework that enables simultaneous iodine and bone decomposition from single-energy X-ray projections acquired with conventional energy-integrating detectors. The model was trained and tested on 1440 groups of energy-integrating detector (EID) projections with their corresponding iodine/bone decomposition images. Experimental results demonstrate that the Dual-head Pix2Pix outperforms baseline models. For iodine decomposition, it achieved a mean absolute error (MAE) of 5.30 ± 1.81, representing an ~10% improvement over Pix2Pix (5.92) and a substantial advantage over CycleGAN (10.39). For bone decomposition, the MAE was reduced to 9.55 ± 2.49, an ~6% improvement over Pix2Pix (10.18). Moreover, Dual-head Pix2Pix consistently achieved the highest MS-SSIM, PSNR, and Pearson correlation coefficients across all benchmarks. In addition, we performed a cross-domain validation using projection images acquired from a conventional EID-CT system. The results show that the model successfully achieved the effective separation of iodine and bone in this new domain, demonstrating a strong generalization capability beyond the training distribution. In summary, Dual-head Pix2Pix provides a cost-effective, scalable, and hardware-friendly solution for accurate dual-material decomposition, paving the way for the broader clinical and industrial adoption of material-specific imaging without requiring PCDs. Full article

Aberrant internal carotid arteries (ICA) are congenital vascular anomalies that occur from involution of the cervical portion of the ICA, which leads to enlargement of the normally small collateral inferior tympanic and caroticotympanic arteries. The inferior tympanic artery is a branch of the external carotid artery, usually the ascending pharyngeal artery, which extends through the inferior tympanic canaliculus (ITC), a small foramen located along the cochlea promontory. Aberrant ICAs can also be associated with a persistent stapedial artery (PSA), which is an abnormal vessel that arises from the petrous ICA and passes through the obturator foramen of the stapes. An aberrant ICA is a very important anomaly to recognize on imaging. Accurately describing its presence is important to help prevent iatrogenic injury during intervention. It is also important to distinguish an aberrant ICA from a lateralized ICA. The improvement of spatial resolution with photon counting detector (PCD)-CT has been proven to provide higher performance in detection of sub-centimeter vascular lesions compared to conventional energy-integrated detector (EID)-CT. PCD-CT also provides superior visualization of small skull-based foramina such as the inferior tympanic canaliculus, which can aid in more accurately characterizing an aberrant ICA (variant course without ITC involvement). Full article

Background/Objectives: Coronary CT angiography (CCTA) is a cornerstone in evaluating stable coronary artery disease (CAD), but conventional energy-integrating detector CT (EID-CT) has limitations, including calcium blooming and limited spatial resolution. Photon-counting detector CT (PCD-CT) may overcome these drawbacks through enhanced spatial resolution and improved tissue characterization. Methods: In this retrospective, propensity score–matched study, we compared CCTA findings from 820 patients (410 per group) who underwent either EID-CT or PCD-CT for suspected stable CAD. Primary outcomes included stenosis severity, high-risk plaque features, and downstream invasive coronary angiography (ICA) referral and yield. Results: The matched cohorts were balanced in demographics and cardiovascular risk factors (mean age 67 years, 63% male). PCD-CT showed a favorable shift in stenosis severity distribution (p = 0.03). High-risk plaques were detected less frequently with PCD-CT (22.7% vs. 30.5%, p = 0.01). Median coronary calcium scores did not differ (p = 0.60). Among patients referred for ICA, those initially evaluated with PCD-CT were more likely to undergo revascularization (62.5% vs. 44.1%), and fewer underwent potentially unnecessary ICA without revascularization (3.7% vs. 8.0%, p = 0.001). The specificity in diagnosing significant stenosis requiring revascularization was 0.74 with EID-CT and 0.81 with PCD-CT (p = 0.04). Conclusions: PCD-CT improved diagnostic specificity for CAD, reducing unnecessary ICA referrals while maintaining detection of clinically significant disease. This advanced CT technology holds promise for more accurate, efficient, and patient-centered CAD evaluation. Full article

Musculoskeletal (MSK) disorders remain a major global cause of disability, with diagnostic complexity arising from their heterogeneous presentation and multifactorial pathophysiology. Recent advances across imaging modalities, molecular biomarkers, artificial intelligence applications, and point-of-care technologies are fundamentally reshaping musculoskeletal diagnostics. This review offers a novel synthesis by unifying recent innovations across multiple diagnostic imaging modalities, such as CT, MRI, and ultrasound, with emerging biochemical, genetic, and digital technologies. While existing reviews typically focus on advances within a single modality or for specific MSK conditions, this paper integrates a broad spectrum of developments to highlight how use of multimodal diagnostic strategies in combination can improve disease detection, stratification, and clinical decision-making in real-world settings. Technological developments in imaging, including photon-counting detector computed tomography, quantitative magnetic resonance imaging, and four-dimensional computed tomography, have enhanced the ability to visualize structural and dynamic musculoskeletal abnormalities with greater precision. Molecular imaging and biochemical markers such as CTX-II (C-terminal cross-linked telopeptides of type II collagen) and PINP (procollagen type I N-propeptide) provide early, objective indicators of tissue degeneration and bone turnover, while genetic and epigenetic profiling can elucidate individual patterns of susceptibility. Point-of-care ultrasound and portable diagnostic devices have expanded real-time imaging and functional assessment capabilities across diverse clinical settings. Artificial intelligence and machine learning algorithms now automate image interpretation, predict clinical outcomes, and enhance clinical decision support, complementing conventional clinical evaluations. Wearable sensors and mobile health technologies extend continuous monitoring beyond traditional healthcare environments, generating real-world data critical for dynamic disease management. However, standardization of diagnostic protocols, rigorous validation of novel methodologies, and thoughtful integration of multimodal data remain essential for translating technological advances into improved patient outcomes. Despite these advances, several key limitations constrain widespread clinical adoption. Imaging modalities lack standardized acquisition protocols and reference values, making cross-site comparison and clinical interpretation difficult. AI-driven diagnostic tools often suffer from limited external validation and transparency (“black-box” models), impacting clinicians’ trust and hindering regulatory approval. Molecular markers like CTX-II and PINP, though promising, show variability due to diurnal fluctuations and comorbid conditions, complicating their use in routine monitoring. Integration of multimodal data, especially across imaging, omics, and wearable devices, remains technically and logistically complex, requiring robust data infrastructure and informatics expertise not yet widely available in MSK clinical practice. Furthermore, reimbursement models have not caught up with many of these innovations, limiting access in resource-constrained healthcare settings. As these fields converge, musculoskeletal diagnostics methods are poised to evolve into a more precise, personalized, and patient-centered discipline, driving meaningful improvements in musculoskeletal health worldwide. Full article